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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<div class="textblock">Here is a list of all typedefs with links to the classes they belong to:</div>

<h3><a id="index_m" name="index_m"></a>- m -</h3><ul>
<li>MatrixType&#160;:&#160;<a class="el" href="classshark_1_1_abstract_loss.html#a87fa1fa41bb3c1d5ce75137428724536">shark::AbstractLoss&lt; LabelT, OutputT &gt;</a>, <a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#a75302b71e238815a8b5c8dc663add783">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_box_constrained_problem.html#ae6ac16940dad311fe5702588be55ce85">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_boxed_s_v_m_problem.html#a2bd43ebb430844ffaf029e4dbe28654b">shark::BoxedSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_c_s_v_m_problem.html#ae00fca2fe283929b4eaf80ca74fc4eeb">shark::CSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_general_quadratic_problem.html#adc77a7278f5f0f3352507ff106170222">shark::GeneralQuadraticProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_linear_classifier.html#a3f38de0d9fa3688f1377c6ab74ab1091">shark::LinearClassifier&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#afa32d6a99e249c080ff0f21f1814c804">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#a4e039c8a44164e2f96137119779ef344">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>Metric&#160;:&#160;<a class="el" href="classshark_1_1_simple_nearest_neighbors.html#ac39c0a94032d08b667e3cb692f514fbd">shark::SimpleNearestNeighbors&lt; InputType, LabelType &gt;</a></li>
<li>ModelBaseType&#160;:&#160;<a class="el" href="classshark_1_1_abstract_model.html#a7fccb0cdf4c0b47afbe5da03532b9b4e">shark::AbstractModel&lt; InputTypeT, OutputTypeT, ParameterVectorType &gt;</a></li>
<li>ModelType&#160;:&#160;<a class="el" href="classshark_1_1_abstract_budget_maintenance_strategy.html#a2fce0a0656e77df1f5e54bea0d3c9f6b">shark::AbstractBudgetMaintenanceStrategy&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#afd9542675b41765f725846a0d9814c5e">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_trainer.html#a0d5c9d35b614d6a33e4e8bfeaf1e9298">shark::AbstractTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_unsupervised_trainer.html#a92fa6ed2ab64402cb414e3c19e9edeaf">shark::AbstractUnsupervisedTrainer&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_abstract_weighted_trainer.html#ad2ad0a52ecd9ac8677df6dbf403b68b4">shark::AbstractWeightedTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_weighted_unsupervised_trainer.html#a0ad676e9aed1a00dc6c4105f29e43426">shark::AbstractWeightedUnsupervisedTrainer&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_cross_validation_error.html#a7c47bbe556f13d936e254971c06997d9">shark::CrossValidationError&lt; ModelTypeT, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_epsilon_svm_trainer.html#a8989b04b8588b9481f1ead75a26fae71">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a62a15b8334075f72a3dfd0827d6d28e5">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#a438d0be0a607dac285103e8a264705ae">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_lasso_regression.html#aaa5953a1525e6777f08097307bf5b792">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#a33d1c1faf1d83e0eac1506daa718ca04">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_logistic_regression.html#a1d653feba69db50f94611dfba14f9d88">shark::LogisticRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_loo_error.html#aeebe3f649a655a693566c209f8fde436">shark::LooError&lt; ModelTypeT, LabelType &gt;</a>, <a class="el" href="classshark_1_1_one_class_svm_trainer.html#a352415c5b0237a1158996985350707bb">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_optimization_trainer.html#a49f97f789b60936b63516cfcba72cab8">shark::OptimizationTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_regularization_network_trainer.html#a681d8e1fad11bcd8a7c8a73c5e1fb38e">shark::RegularizationNetworkTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_squared_hinge_c_svm_trainer.html#ad69153c70a470b6e40b73e746c578fa9">shark::SquaredHingeCSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_variational_autoencoder_error.html#a1bcef582ede4db4936b7d6191949000d">shark::VariationalAutoencoderError&lt; SearchPointType &gt;</a></li>
<li>MultiTaskSampleType&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_task_kernel.html#a74d917dde073cfd8b0e089073191458d">shark::GaussianTaskKernel&lt; InputTypeT &gt;</a></li>
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